Este curso forma parte de Programa especializado: Machine Learning for Trading

4.0
estrellas
777 calificaciones

87 %

Jack Farmer

40.940 ya inscrito

Ofrecido Por

Google Cloud

Instituto de Finanzas de Nueva York

Programa especializado: Machine Learning for TradingGoogle Cloud

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In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks. 
To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging).

Fechas límite flexibles

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Certificado para compartir

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100 % en línea

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Laboratorios de Coursera

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Curso 1 de 3 en

Programa especializado: Machine Learning for Trading

Nivel intermedio

Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.

Aprox. 9 horas para completar

Inglés (English)

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Prueba Coursera para negocios

Qué aprenderás

Understand the fundamentals of trading, including the concepts of trend, returns, stop-loss, and volatility.
Define quantitative trading and the main types of quantitative trading strategies.
Understand the basic steps in exchange arbitrage, statistical arbitrage, and index arbitrage.
Understand the application of machine learning to financial use cases.

Habilidades que obtendrás

Finance
Trading
Investment
Machine Learning applied to Finance

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Laboratorios de Coursera

Incluye proyectos de aprendizaje prácticos.

Obtén más información sobre los laboratorios de Coursera

Curso 1 de 3 en

Programa especializado: Machine Learning for Trading

Nivel intermedio

Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.

Aprox. 9 horas para completar

Inglés (English)

¿Podría tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?

Prueba Coursera para negocios

Instructor

Calificación del instructor

4,41/5 (164 calificaciones)

Jack Farmer

Curriculum Director

New York Institute of Finance

83.719 alumnos

11 cursos

Ofrecido por

Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.

Instituto de Finanzas de Nueva York

The New York Institute of Finance (NYIF), is a global leader in training for financial services and related industries. Started by the New York Stock Exchange in 1922, it now trains 250,000+ professionals in over 120 countries. NYIF courses cover everything from investment banking, asset pricing, insurance and market structure to financial modeling, treasury operations, and accounting. The institute has a faculty of industry leaders and offers a range of program delivery options, including self-study, online courses, and in-person classes. Its US customers include the SEC, the Treasury, Morgan Stanley, Bank of America and most leading worldwide banks.

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Programa - Qué aprenderás en este curso

Calificación del contenido87%(3,610 calificaciones)

Semana1

Semana 1

4 horas para completar

Introduction to Trading with Machine Learning on Google Cloud

4 horas para completar

26 videos (Total 131 minutos), 3 lecturas, 5 cuestionarios

26 videos

Class Overview - Who these courses are for1mCourse Overview Introduction to Trading with Machine Learning on Google Cloud5mWhat is AI and ML ? What is the difference between AI and ML?58sApplications of ML in the Real World1mWhat is ML?3mGame: The importance of good data4mBrief History of ML in Quantitative Finance11mWhy Google?1mWhy Google Cloud Platform?2mWhat are AI Platform Notebooks1mUsing Notebooks1mBenefits of AI Platform Notebooks2mWhat do we want to model? Let's start simple5mDemo: Building a model with BigQuery ML25mHow to use Qwiklabs for your Labs3mLab Intro: Building a Regression Model37sLab Walkthrough: Building a Regression Model9mTrading vs Investing6mThe Quant Universe2mQuant Strategies7mQuant Trading Advantages and Disadvantages4mExchange and Statistical Arbitrage8mIndex Arbitrage2mStatistical Arbitrage Opportunities and Challenges5mIntroduction to Backtesting5mBacktesting Design6m

3 lecturas

Supervised Learning and Regression10mWelcome to Introduction to Trading, Machine Learning and GCP10mCase Study: Capital Markets in the Cloud10m

4 ejercicios de práctica

Python Skills Assessment QuizAI and Machine Learning5mGoogle CloudTrading Concepts Review15m

Semana2

Semana 2

3 horas para completar

Supervised Learning with BigQuery ML

3 horas para completar

6 videos (Total 29 minutos), 1 lectura, 3 cuestionarios

Semana3

Semana 3

2 horas para completar

Time Series and ARIMA Modeling

2 horas para completar

11 videos (Total 52 minutos)

11 videos

What is a time series?7mAR - Auto Regressive7mMA - Moving Average2mThe Complete ARIMA Model4mARIMA compared to linear regression7mHow can you get a variety of models from just a single series?1mHow to choose ARIMA parameters for your trading model4mTime Series Terminology: Auto Correlation4mSensitivity of Trading Strategy4mLab Intro: Forecasting Stock Prices Using ARIMA32sLab Walkthrough: Forecasting Stock Prices using ARIMA7m

1 ejercicio de práctica

Time Series

Semana4

Semana 4

1 hora para completar

Introduction to Neural Networks and Deep Learning

1 hora para completar

5 videos (Total 29 minutos), 1 lectura, 2 cuestionarios

Reseñas

4.0

206 reseña

5 stars
44,54 %
4 stars
30,03 %
3 stars
14,37 %
2 stars
4,36 %
1 star
6,67 %

Principales reseñas sobre INTRODUCTION TO TRADING, MACHINE LEARNING & GCP

por MA25 de dic. de 2019

Would be nice to have some extra step at the end of the lad to actually build a trading strategy instead of stopping at the fitting of the model

por AM7 de mar. de 2020

Great for beginners! A lot of examples and theories with practices. It let me learn more about the underlying principles.

por IP8 de jul. de 2021

Great introductory course to give you the taste of what lies ahead. Not a stand alone, as does not provide sufficient knowledge to build DNN on financial data.

por MS29 de ene. de 2020

Excellent! But, I am missing some of the prerequisites since I just wanted to take a chance and try things out, but feel like proceeding further might lead to some stumbling blocks.

Ver todas las reseñas

Acerca de Programa especializado: Machine Learning for Trading

This 3-course Specialization from Google Cloud and New York Institute of Finance (NYIF) is for finance professionals, including but not limited to hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning (ML) and Python. Alternatively, this program can be for Machine Learning professionals who seek to apply their craft to quantitative trading strategies. By the end of the Specialization, you'll understand how to use the capabilities of Google Cloud to develop and deploy serverless, scalable, deep learning, and reinforcement learning models to create trading strategies that can update and train themselves. As a challenge, you're invited to apply the concepts of Reinforcement Learning to use cases in Trading. This program is intended for those who have an understanding of the foundations of Machine Learning at an intermediate level. To successfully complete the exercises within the program, you should have advanced competency in Python programming and familiarity with pertinent libraries for Machine Learning, such as Scikit-Learn, StatsModels, and Pandas; a solid background in ML and statistics (including regression, classification, and basic statistical concepts) and basic knowledge of financial markets (equities, bonds, derivatives, market structure, and hedging). Experience with SQL is recommended.

Preguntas Frecuentes

¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Hay ayuda económica disponible?
Sí. En ciertos programas de aprendizaje, puedes postularte para recibir ayuda económica o una beca en caso de no poder costear los gastos de la tarifa de inscripción. Si hay ayuda económica o becas disponibles para tu selección de programa de aprendizaje, verás un enlace para postularte en la página de descripción.

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Introduction to Trading, Machine Learning & GCP

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Qué aprenderás

Habilidades que obtendrás